Duplicate Detection Evaluation
Duplicate Detection Evaluation is a scholarly assessment framework that systematically measures the effectiveness, accuracy, and reliability of duplicate detection methods by defining specific metrics, benchmarks, and validation protocols to distinguish true duplicates from non-duplicates within a given dataset.
92
Publications
5.3K
Citations
263
Authors
113
Institutions
Publications per year
2017–2026
29
Parents
92
Detecting near-duplicates for web crawling
Gurmeet Singh Manku, Arvind Kumar Jain, Anish Das Sarma · 2007 · 610 citations
Finding near-duplicate web pages
Monika Henzinger · 2006 · 434 citations · Full text
Péter Jacsó · Online Information Review · 2008 · 208 citations
1–5 of 92
263
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113

The University of Melbourne
Melbourne, Australia
5 h-index
17 publications
520 citations
Queen's University
Kingston, Canada
4 h-index
11 publications
788 citations
Hasso Plattner Institute
Potsdam, Germany
4 h-index
11 publications
301 citations
Microsoft (United States)
Redmond, United States
3 h-index
6 publications
583 citations
University of Potsdam
Potsdam, Germany
3 h-index
7 publications
191 citations
Google (United States)
Mountain View, United States
3 h-index
9 publications
1.8K citations

Bangor University
Bangor, United Kingdom
2 h-index
2 publications
90 citations

University of Hawaii System
Honolulu, United States
2 h-index
2 publications
292 citations
1–8 of 113
3 publications · 332 citations
3
h-index
3 publications · 432 citations
3
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Repository · 2 publications · 34 citations
2
h-index
2 publications · 128 citations
2
h-index
2 publications · 29 citations
2
h-index
1–5